Exploring functional connectivity in large-scale brain networks in obsessive-compulsive disorder: a systematic review of EEG and fMRI studies

Abstract Obsessive-compulsive disorder (OCD) is a debilitating psychiatric condition that is difficult to treat due to our limited understanding of its pathophysiology. Functional connectivity in brain networks, as evaluated through neuroimaging studies, plays a pivotal role in understanding OCD. While both electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have been extensively employed in OCD research, few have fully synthesized their findings. To bridge this gap, we reviewed 166 studies (10 EEG, 156 fMRI) published up to December 2023. In EEG studies, OCD exhibited lower connectivity in delta and alpha bands, with inconsistent findings in other frequency bands. Resting-state fMRI studies reported conflicting connectivity patterns within the default mode network (DMN) and sensorimotor cortico-striato-thalamo-cortical (CSTC) circuitry. Many studies observed decreased resting-state connectivity between the DMN and salience network (SN), implicating the 'triple network model' in OCD. Task-related hyperconnectivity within the DMN-SN and hypoconnectivity between the SN and frontoparietal network suggest OCD-related cognitive inflexibility, potentially due to triple network dysfunction. In conclusion, our review highlights diverse connectivity differences in OCD, revealing complex brain network interplay that contributes to symptom manifestation. However, the presence of conflicting findings underscores the necessity for targeted research to achieve a comprehensive understanding of the pathophysiology of OCD.


Introduction
Obsessive-compulsive disorder (OCD), affecting approximately 2-3% of the global population (Kessler et al. 2012), presents a complex mental health challenge characterized by the presence of distressing obsessions and compulsions (Stein et al. 2019).OCD exerts a profound impact on various aspects of an individual's life, with compulsions often demanding a significant time commitment, disrupting daily activities and relationships, thereby compromising overall quality of life (Remmerswaal et al. 2016).The total annual economic burden of OCD was estimated to be US$8.4 billion in the United States, accounting for 5.7% of the cost of treating psychiatric conditions (DuPont et al. 1995).Furthermore, Swedish national survey data show that 11% of OCD patients have been unemployed for over 180 days each year (Pérez-Vigil et al. 2019).
Accepted treatment approaches for OCD primarily involve a combination of pharmacotherapy and psychotherapy.While these traditional treatments have proven effective for many individuals, a significant portion (up to 60%) may not respond adequately (Taylor et al. 2012).This treatment resistance has prompted exploration into alternative approaches, such as transcranial magnetic stimulation (TMS) (Perera et al. 2021), transcranial alternating current stimulation (tACS) (Perera et al. 2023a) and deep brain stimulation (DBS) (Alonso et al. 2015).These therapies are believed to operate by modulating the functional connections within the brain.
Although substantial research has been conducted, the underlying pathophysiological mechanisms of OCD are still not fully understood, which has hindered development of effective treatments.Therefore, there is a critical unmet need to uncover the pathophysiological basis of OCD, which will ultimately pave the way for more effective targeted treatments.The brain is thought to process information, control functions and generate thoughts, emotions and behaviors through interactions within and between intricate networks (Bullmore and Sporns 2009).Prior research extensively investigates the hypothesis that OCD stems from dysfunctional neurocircuitry, marked by abnormal interactions within and between various brain structures.Neuroimaging techniques such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have shown electrophysiological and structural differences in OCD (Menzies et al. 2008;Perera et al. 2019).These findings encompass differences in EEG-measured oscillations (Perera et al. 2023b), event-related potentials (Perera et al. 2023c), and fMRI-measured brain volumes and blood f low activations (Menzies et al. 2008).However, the examination of temporal correlations and interactions between brain regions necessitates the use of functional connectivity (FC) measures, typically conducted through techniques such as EEG or, more commonly, fMRI.FC refers to statistical dependencies or correlations between different brain regions or neural populations and is a measure of the synchronized activity between these regions (Craddock et al. 2015).
Alterations in FC within and between brain networks in OCD have been reported in many studies.Several brain networks have been consistently reported as dysfunctional in OCD.One prominent example is the default mode network (DMN), a large-scale brain network that is active during wakeful rest or while processing detailed thoughts related to external task performance (Raichle 2015).The cortico-striato-thalamo-cortical (CSTC) circuitry includes multiple sub-circuits (e.g.limbic, sensorimotor, dorsal attention loops) which play pivotal roles in a range of brain functions (Graybiel and Rauch 2000).The salience network (SN), plays a crucial role in directing attention and prioritizing stimuli based on their emotional or sensory significance (Seeley 2019).Finally, the frontoparietal network (FPN), is comprised of a complex group of brain regions related to attention, working memory and cognitive control (Marek and Dosenbach 2022).A large body of research reports that dysconnectivity within CSTC circuits is involved in the pathophysiology of OCD (Pauls et al. 2014).However, aberrant FC between the DMN, SN and FPN has also been linked to a "triple network model" (TNM) of psychopathology in OCD (Fan et al. 2017a).In this model, the SN acts as a mediator between the FPN and the DMN, which are anticorrelated to each other (when one network is active, the other is suppressed).
A meta-analysis of resting-state network FC in OCD reported dysconnectivity between the DMN, SN and FPN, providing evidence for the TNM dysfunction model in OCD (Gürsel et al. 2018).Another recent meta-analysis has provided supporting evidence towards the traditional dysfunctional CSTC with findings of dysconnectivity within the fronto-limbic CSTC subcircuit (Liu et al. 2022).Furthermore, a systematic review of 20 resting-state fMRI studies highlighted the role of impaired DMN and FPN connectivity in OCD (Fornaro and Vallesi 2023).However, these reviews have not collectively assessed all available studies, and all omitted task-related fMRI findings from their analyses.Task-related fMRI findings offer valuable insights into dynamic changes in brain activity during specific cognitive tasks, enhancing our understanding of neural mechanisms in OCD.Furthermore, a comprehensive review of EEG connectivity findings in OCD has not been performed to date.The current systematic review aims to fill this gap by comprehensively collating EEG and fMRI data, and critically evaluating FC differences in OCD compared to healthy controls (HC).Additionally, we discuss the limitations of EEG and fMRI individually, and explore the potential benefits of integrating the two modalities to acquire simultaneous EEG-fMRI data in future studies.This novel approach aims to enhance our ability to comprehend the underlying neurophysiology of OCD.Furthermore, the categorization of studies based on large-scale brain networks and analysis of the consistency of altered FC findings will collectively enhance our understanding of the neurophysiological patterns associated with OCD.This approach will provide a more nuanced and comprehensive perspective, ultimately suggesting potential brain targets for future treatments.

Search strategy
A search of the relevant literature was performed adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (McInnes et al. 2018).A primary search was performed using several electronic databases including MEDLINE, PubMed, Scopus, PsycINFO and Web of Science.Studies published in English up to December 2023 were included.The keywords used for the initial search were obsessivecompulsive disorder, OCD, electroencephalography, EEG, functional magnetic resonance imaging, fMRI, functional connectivity, FC and brain networks.After identifying key networks implicated in OCD through an initial literature search, search terms were expanded to include additional keywords such as default mode network, DMN, salience network, SN, frontoparietal network, FPN, cortico-striato-thalamo-cortical circuit and CSTC.The obtained results were imported into Covidence (https://www.covidence.org/) to facilitate abstract screening, full-text review, and study extraction.A second reviewer (ESG) was involved in the study screening process.Records for which reviewers had opposing decisions were reviewed together and a consensus was formed.

Study selection
The inclusion criteria were: (1) availability of full-length articles published in peer-reviewed journals; (2) inclusion of participants with a primary diagnosis of OCD or obsessive-compulsive personality disorder; (3) availability of a detailed description of EEG/fMRI methods and results; (4) the study involved analysis of FC in OCD participants with a comparison sample of HC (note that FC excludes structural MRI examinations of connectivity).Studies conducted with both pediatric and adult populations were included.Initially, all identified articles were included following inspection of the title and the abstract.Thereafter, full-text versions were assessed in more detail to exclude ineligible articles.Additional relevant articles were identified through manual searching of the reference lists of the selected articles.The study inclusion and exclusion procedures are summarized in Fig. 1.

Data extraction
The following information was extracted and recorded from the included studies: (1) year of publication; (2) EEG/fMRI technique (resting-state or task-related); (3) key findings.The following characteristics of participants in each study were recorded: (a) sample size (experimental and control groups); (b) mean age; (c) male:female ratio.The studies were initially grouped based on the neuroimaging technique (EEG or fMRI).fMRI studies were further grouped based on resting-state/task and specific largescale brain networks based on their findings.The key findings of each study within each group were extracted to facilitate qualitative analysis, aiming to elucidate the pathophysiology of OCD.In cases where studies did not report specific brain networks involved, the reported brain regions were mapped to commonly accepted functional networks based on widely used atlases such as Yeo's 7-and 17-network parcellations (Schaefer et al. 2018;Yeo et al. 2011).The brain regions associated with each identified network are highlighted in Supplementary Table S1.The principal FC analysis technique used in each fMRI study is shown in Supplementary Tables S4 and S5.

Quantitative analysis
A quantitative assessment was conducted exclusively for restingstate fMRI studies to evaluate the consistency of reporting for each finding.Findings indicating higher or lower FC within and between brain networks compared to HC were identified and compiled.Subsequently, the total number of participants with OCD included in each study was summed to derive a final cumulative count for each identified connectivity finding.These cumulative sums were used to generate chord diagrams representing the number of OCD patients that showed the relevant inter/intranetwork connectivity finding (Krzywinski et al. 2009).This analysis was not extended to EEG and task-related fMRI studies due to the limited number of available studies and the heterogeneity between studies, respectively.

Results
The final eligible list included 166 studies (10 EEG studies and 156 fMRI studies).The fMRI studies were further categorized into resting-state (125 studies) and task-related (31 studies) findings.

EEG studies
Table 1 summarizes the OCD and HC participant data and key findings of the EEG studies.All studies reported EEG findings while participants were at rest.Two studies reported significantly lower FC within the delta frequency band (Perera et al. 2023b;Özçoban et al. 2018).Perera et al. (2023b) found reduced delta FC in frontocentral and centroparietal electrodes, while Özçoban et al. (2018) reported decreased delta FC in frontal scalp regions.In contrast, one study reported increased theta FC in the frontooccipital regions compared to HC (Desarkar et al. 2007).FC within the alpha band was found to be decreased consistently (Choi et al. 2021;Tan et al. 2019;Tan et al. 2022;Velikova et al. 2010).Choi et al. (2021) noted reduced FC within DMN nodes, while Velikova et al. (2010) and Tan et al. (2022) observed decreased inter-hemispheric alpha FC in frontal, central, and temporal electrodes.Beta band FC exhibited conf licting findings across studies, with two reporting decreased FC (Choi et al. 2021;Olbrich et al. 2013) and one indicating an increase in beta FC within bilateral posterior regions (Tan et al. 2019).The discrepancy extends to the localisation of decreased beta FC, with one study identifying it within the DMN (Choi et al. 2021), while another pinpointed it specifically within frontal areas, excluding the DMN (Olbrich et al. 2013).Three studies (Saifutdinova et al. 2016;Tan et al. 2022;Özçoban et al. 2018) reported overall decreased FC globally in OCD groups compared to HC.
Within EEG studies reviewed, only two reported FC findings related to FC within large-scale brain networks (Choi et al. 2021;Olbrich et al. 2013).Choi et al. (2021) reported significantly lower FC within the DMN, while Olbrich et al. (2013) reported no difference in FC within the DMN in OCD when compared to HC.This finding is consistent with the results from fMRI studies discussed later, where decreased FC within the DMN was found to be a major finding in resting-state fMRI studies of OCD (Beucke et al. 2014;Fan et al. 2023;Wang et al. 2019).

Resting-state fMRI studies
Table 2 summarizes key findings of resting-state fMRI studies.Figure 2 presents the chord diagrams depicting findings of the quantitative analysis described in Section 2.4.The values used to create the diagrams are presented in Supplementary Table S2.In the decreased FC section (Fig. 2a), the most consistently reported finding across studies was within the DMN, with a total of 525 OCD participants across 10 studies supporting this conclusion.This was followed by decreased FC within the sensorimotor CSTC circuit, a finding supported by a total of 381 OCD participants across 7 studies.Within the analyses of inter-network FC, the most Note.OCD-obsessive-compulsive disorder, EEG-electroencephalography, M-male, F-female, y-years old, SD-standard deviation, HC-healthy controls, DMN-default mode network, r-right, l-left, SFG-superior frontal gyrus, ACC-anterior cingulate cortex, MFG-medial frontal gyrus, wPLI-weighted phase lag index, FC-functional connectivity.
OCD-obsessive-compulsive disorder, fMRI-functional magnetic resonance imaging, M-male, F-female, y-years old, SD-standard deviation, NAc-nucleus accumbens, mPFC-medial prefrontal cortex, lPFC-lateral prefrontal cortex, CSTC-cortico-striato-thalamo-cortical, VMC-ventral motivational circuit, dACC-dorsal anterior cingulate cortex, l-left, r-right, BL-bilateral, DLPFC-dorsolateral prefrontal cortex, FPN-frontoparietal network, vmPFC-ventromedial prefrontal cortex, OFC-orbitofrontal cortex, SM-sensorimotor, DC-dorsal cognitive, OCPD-obsessive-compulsive personality disorder, PCC-posterior cingulate cortex, VN-visual network, SMA-supplementary motor area, AI-anterior insula.consistent finding was decreased inter-network FC between the DMN and SN with a total of 285 OCD participants across 7 studies providing evidence for this result.As presented in Fig. 2b, the most consistent findings among studies that reported increased intranetwork FC was within the DMN with a total of 528 participants across 15 studies, followed by increased FC within the sensorimotor CSTC with a total of 458 participants across 10 studies.The most consistent finding of increased inter-network FC was found between the DMN-cerebellum with a total of 269 OCD participants across 5 studies.

Task-related fMRI studies
Table 3 summarizes participant data, task paradigms and key findings of task-related fMRI studies in OCD.The most consistently reported finding among task-related studies was an increase in FC within the FPN, observed in a total of 177 OCD patients across three studies that used set shifting or task switching paradigms.The most consistent finding among studies reporting decreased FC was observed between the limbic CSTC circuit and the DMN, involving a total of 59 OCD participants across two studies.

Discussion
In this review, findings from both EEG and fMRI FC studies in OCD were meticulously examined and synthesized.Within EEG studies, significantly lower FC was consistently observed within the delta and alpha frequency bands in OCD groups compared to HC, while results in the theta and beta bands were less conclusive.Contradictory reports emerged from resting-state fMRI studies, revealing both higher and lower FC within the DMN and the sensorimotor CSTC circuit.Notably, many studies reported lower connectivity between the DMN and SN at rest, suggesting potential impairments of the TNM underlying OCD symptoms.Task-related hyperconnectivity between the DMN-SN and hypoconnectivity between the SN-FPN further suggest cognitive inf lexibility in OCD, possibly stemming from dysfunction within the TNM.Slow delta band oscillations provide important information on both motivational and cognitive processes such as memory, attention, decision-making and planning (Sauseng and Klimesch 2008).Impaired FC within the delta band (Perera et al. 2023b;Özçoban et al. 2018) is related to the subcortical centres generating delta band activity such as the medial prefrontal cortex (mPFC) and orbitofrontal cortex (Murphy et al. 2009b), both of which are vital areas of the CSTC circuits that are implicated in the pathophysiology of OCD (Milad and Rauch 2012).Therefore, lower delta FC within CSTC circuitry may ref lect a pathophysiological marker that potentially underpins the clinical symptoms of OCD.Additionally, it is noteworthy that the only study focusing on theta band FC reported a significant increase in fronto-occipital FC (Desarkar et al. 2007).Research has found significant positive correlation between increased EEG coherence and increased subcortical metabolic activity (Newton et al. 1993).Furthermore, there is strong neuroimaging evidence of heightened metabolic activity in subcortical structures such as the basal ganglia and thalamus in OCD groups (Saxena and Rauch 2022).Therefore, the higher theta coherence may ref lect overactivity within subcortical circuitry in OCD.However, this study used coherence as the sole connectivity measure, and did not follow optimal EEG connectivity analysis methods highlighted in a recent guideline (Miljevic et al. 2021).Therefore, further research is required to arrive at reliable conclusions regarding theta band connectivity in OCD.

Key findings from EEG studies
Lower FC within the alpha band compared to HC was reported in 4 out of 10 studies (Choi et al. 2021;Tan et al. 2019;Tan et al. 2022;Velikova et al. 2010).One study that utilized source localisation found decreased alpha connectivity localized mainly within the DMN, predominantly connections involving the posterior cingulate cortex (PCC) (Choi et al. 2021).Research suggests that alterations in PCC activity may contribute to perseveration of obsessive thoughts and rumination commonly observed in OCD patients (Makovac et al. 2020).Furthermore, previous reports indicate that gray matter volume and resting-state metabolism within the PCC are higher in OCD groups compared to HC (Brennan et al. 2016;Hou et al. 2013).Consequently, it might be hypothesized that impaired FC within the PCC could lead to excessive obsessive rumination, while the observed increases in gray matter volume and metabolism might serve as compensatory mechanisms to mitigate this effect.However, in contrast to our findings of lower alpha band FC in OCD, previous research on major depressive disorder has reported significantly increased alpha band FC. (Miljevic et al. 2023).This suggests that the decreased alpha FC shown in OCD is unlikely to be attributed to comorbid depression but may instead represent a finding specifically associated with OCD.
Beta FC was also found to be significantly lower in OCD compared to HC (Olbrich et al. 2013;Yazdi-Ravandi et al. 2018).Beta band connectivity is associated with memory encoding, retrieval and maintenance of information (Palva et al. 2010).In this context, decreased connectivity within the beta band in the frontal brain regions during high vigilance states in OCD (Olbrich et al. 2013) may be related to previously reported dysfunction within these cognitive domains in individuals with OCD (Deckersbach et al. 2000).In contrast, one study reported increased beta FC in the OCD group during the eyes-open state (Tan et al. 2019).The authors attributed this finding to impaired suppression of recurrent, unwanted thoughts leading to excessive stress and anxiety (Vul et al. 2009).Furthermore, their findings were thought to provide evidence towards the abnormal small-world
architecture within OCD patients.Small-world architecture refers to the efficient organization of neural connections that enables both specialized processing within local brain regions and rapid communication between distant brain regions (Bassett and Bullmore 2006).Tan et al. (2019) found elevated shortrange beta FC within occipital regions and reduced alpha FC in long-range connections, supporting this finding (Tan et al. 2019).However, it is known that beta band findings are highly prone to muscle artifacts (Muthukumaraswamy 2013).Therefore, if muscle artifacts were not sufficiently controlled for by the EEG pre-processing, this confound may have contributed to the contradicting findings.Furthermore, it should be noted that EEG measures reconstructed from sparsely sampled sensor signals on the scalp into the three-dimensional brain space can result in source activity seeping into adjacent regions, which can distort connectivity measures (Palva et al. 2018).In contrast, the more accurate source identification of the brain connectome using fMRI has provided useful and meaningful information to explain a wide range of pathological conditions, including OCD (Friston 2002;Gürsel et al. 2018;Iwabuchi et al. 2015).

Resting-state fMRI connectivity
The default mode network Our review acknowledges the conf lict between findings of both higher and lower resting-state FC within the DMN in OCD, highlighting the complexity of neural activity patterns in this network.However, despite contradictory findings (i.e. higher FC in some studies and lower FC in others), it is worth noting that studies revealing lower DMN FC in OCD commonly localized this to anterior regions (Beucke et al. 2014;Fan et al. 2023;Jang et al. 2010), while those indicating higher DMN FC in OCD often pinpoint it to posterior regions (Coutinho et al. 2016;Fan et al. 2017a).This observation suggests that OCD may affect DMN FC differently depending on the brain regions within the DMN.This perspective aligns with recent research challenging the notion of the DMN as a uniform and cohesive system, suggesting a developing understanding of its functional organization in OCD.
Decreased resting-state FC within the DMN in OCD groups compared to HC was reported in a large number of studies (10 in 25 studies that examined the DMN) (Beucke et al. 2014;Cui et al. 2020;Fan et al. 2023;Jang et al. 2010;Ma et al. 2022;Peng et al. 2014a;Peng et al. 2014b;Shan et al. 2019;Wang et al. 2019;Xu et al. 2023a).Additionally, one EEG study (Choi et al. 2021) also reported decreased beta-band FC within the DMN.The convergence of these results across EEG and fMRI modalities underscores the robustness of DMN connectivity alterations in OCD.The DMN is activated when individuals engage in internally focused thoughts, such as self-referential thoughts, autobiographical memory retrieval or envisioning the future (Gusnard et al. 2001).Therefore, the DMN is believed to play a crucial role in supporting adaptable mental simulations related to oneself and aiding in the retrieval of episodic memories, which serves the purpose of utilizing past experiences, and anticipating and assessing future events (Buckner et al. 2008).Individuals with OCD are known to be preoccupied with intrusive and persistent obsessions that are linked to negative external stimuli.Cognitive inf lexibility arising from rigid conceptual frameworks has also been recognized as a cognitive trait characteristic of OCD (Gu et al. 2008).Therefore, it can be conceptualized that impaired DMN connectivity might render f lexible mental simulations difficult for OCD patients.
It is noteworthy that several studies have localized the decreased FC to the anterior regions of the DMN, such as the mPFC (Beucke et al. 2014;Fan et al. 2023;Jang et al. 2010).From a clinical standpoint, OCD often involves abnormal cognitive processing related to the self.Obsessions, in particular, are typically experienced as ego-dystonic, meaning their content contradicts the patient's self-perception (Purdon and Clark 1999).Given that the mPFC is implicated in the mental representation of the self and the certainty of self-view (D'Argembeau et al. 2012), reduced connectivity in this brain region may hinder the ability to dissociate from obsessional content.This impaired recruitment of the mPFC self-system could potentially contribute to the occurrence of obsessive, ego-dystonic thoughts.
Furthermore, another study that reported decreased restingstate FC within the DMN (Peng et al. 2014b), demonstrated that unaffected siblings of OCD participants also exhibited impairments in FC within the PCC, a vital node of the DMN.Furthermore, impaired cognitive f lexibility and motor inhibition were found in relatives of OCD patients (Chamberlain et al. 2007), both traits that are known to be linked to the PCC (Pearson et al. 2011).However, further research is essential to clarify the specific FC findings within the PCC in first-degree relatives, potentially providing brain-based markers for OCD and aiding in the identification of risk genes.
Intriguingly, a large body of literature (15 in 25 studies that examined the DMN) has also reported increased intra-network FC within the DMN (Coutinho et al. 2016;Fan et al. 2017a;Göttlich et al. 2015;Hou et al. 2013;Hou et al. 2014;Kinay et al. 2021;Koçak et al. 2012;Luo et al. 2021;Park et al. 2022;Shi et al. 2021;Takagi et al. 2017;Tang et al. 2023;Tikoo et al. 2020;Weber et al. 2014;Xu et al. 2023b).Recent imaging studies reveal a nuanced perspective on the DMN, challenging the notion of it being a uniform system.Instead, findings suggest a dissociation within the DMN, where the anterior component exhibits heightened activity during self-referential and emotional tasks, while the posterior regions become more prominent during tasks related to episodic memory and perceptual processing (Coutinho et al. 2016;Zhu et al. 2012).Several studies have reported the increase in intra-network FC to be localized to the posterior DMN regions, such as the precuneus (Coutinho et al. 2016) and superior parietal gyrus (Fan et al. 2017a).Therefore, abnormally high posterior DMN FC may be functionally linked to deficits in episodic memory that are present in OCD patients.Episodic memory is crucial for everyday belief updating (Davies and Coltheart 2000), and individuals with OCD often harbor irrational beliefs which can underpin their obsessivecompulsive symptoms.The observed deficits in episodic memory may align with the clinical observation that OCD patients struggle to form or utilize episodic memories to correct their obsessivecompulsive beliefs.

Cortico-striato-thalamo-cortical circuits
Altered FC within the sensorimotor and limbic sub-circuits were found to be the most consistently reported findings within the CSTC loops.The sensorimotor CSTC circuit connects the premotor cortex, putamen and thalamus and mediates transitions from goal-directed behaviors to habitual behaviors and automatic responses (Boedhoe and van den Heuvel 2018;van den Heuvel et al. 2016).Several studies have documented decreased connectivity within the Sensorimotor CSTC in OCD groups compared to HC (Cui et al. 2020;Deng et al. 2019;Lv et al. 2022;Moreira et al. 2019;Sha et al. 2020b;Xu and Zhang 2023;Yang et al. 2019).It is known that individuals with OCD have impaired sensorimotor functions such as sensory gating (Ahmari et al. 2012;Rossi et al. 2005), indicating the potential relevance of this circuit in the pathophysiology of OCD.Conversely, several studies have also reported significantly higher FC within the sensorimotor CSTC circuitry in OCD groups compared to HC (Armstrong et al. 2016;Cano et al. 2018;Chen et al. 2019;Hou et al. 2013;Kim et al. 2019;Park et al. 2020;Tikoo et al. 2020;Xu et al. 2021;Ye et al. 2020;Zhao et al. 2021).Moreover, the postcentral gyrus and supramarginal gyrus, which are both vital nodes of the sensorimotor CSTC circuit, have been found to show greater gray matter volume, metabolic rates and gyrification in OCD patients compared to HC (Subirà et al. 2015;Tang et al. 2016).However, one study reporting raised sensorimotor CSTC connectivity found the increased FC to be negatively correlated to OCD clinical symptom severity (Park et al. 2020).Therefore, it may be that the increased connectivity between sensorimotor CSTC regions ref lects a compensatory mechanism for obsessive-compulsive symptoms rather than contributing towards the pathogenesis of OCD.
The limbic system includes subcortical structures such as the amygdala, as well as cortical structures such as the vmPFC, and is thought to play a major role in the regulation of emotion, memory and spatial orientation (Catani et al. 2013).Decreased FC within the limbic CSTC circuitry was identified in several studies (Anticevic et al. 2014;Cyr et al. 2021;Fullana et al. 2017;Göttlich et al. 2014;Haynes et al. 2018;Posner et al. 2014;Zhao et al. 2021).Functional integration within this limbic CSTC network is thought to mediate reinforcement learning (Bogacz and Larsen 2011;Costa 2007) and behavioral selection via connections to the basal ganglia (Graybiel 1998), the disturbance of which could explain why OCD patients choose inappropriate actions for specific circumstances, as a result of an inability to use new conditions as cues to update behavior (Figee et al. 2011), leading to the repetition of compulsions and cognitive rigidity (Bradbury et al. 2011).However, contradictory findings of enhanced connectivity within the limbic CSTC have also been reported (Apergis-Schoute et al. 2018;Calzà et al. 2019;de Vries et al. 2019;Kim et al. 2019;Yang et al. 2019).Hou et al. (2014) suggested that increased limbic FC may be an endophenotype for OCD as the finding was not correlated with disease severity and both patients and unaffected relatives showed similar differences compared to HC (Hou et al. 2014).Furthermore, the cortical structures of the limbic system (vmPFC) are thought to play a role in the regulation of emotions through implicit inhibitory control over the amygdala (Etkin et al. 2011).Therefore, increased connectivity between the cortical and subcortical limbic structures may imply an increased implicit effort to regulate emotions at rest, ref lecting a compensatory mechanism rather than a pathophysiological marker (de Vries et al. 2019).

Inter-network connectivity and the "triple network model"
While traditional perspectives have associated alterations within individual brain networks with the pathophysiology of OCD (Vythilingum and Stein 2003), recent insights emphasize the inadequacy of these models in accounting for the complex interactions with other brain regions (Reess et al. 2016).In this context, the most consistently reported inter-network connectivity finding in our review was decreased FC between the DMN and SN (Chen et al. 2018;Geffen et al. 2022;Luo et al. 2021;Shi et al. 2021;Versace et al. 2019;Zhang et al. 2011;Zhou et al. 2022), both of which are vital networks within the TNM.The TNM encompasses the FPN (linked to external processes and goal-driven actions), DMN (associated with internal processes and self-referential thoughts) and SN (involved in switching between internal attention and goal-oriented behavior).In this conceptual framework, the SN functions as an intermediary between the FPN and the DMN, both of which exhibit an anticorrelated relationship; when one network is active, the other undergoes suppression.Poor connectivity between the DMN and SN may be associated with OCD patients' difficulty in disengaging from internal self-referential thoughts to adapt to the changing external environment, which could present as both cognitive and behavioral disturbances simultaneously (Fan et al. 2017a).Additionally, reduced SN-DMN connectivity may contribute towards decreased sustained attention (Posner et al. 2017) and poor insight (Fan et al. 2017b) in individuals with OCD.Furthermore, several studies have reported hyperconnectivity between the SN and FPN in the OCD group compared to HC (Fan et al. 2017a;Li et al. 2012;Xu et al. 2023a;Yun et al. 2017;Zhou et al. 2022).This could be related to the known maladaptive cognitive performance in OCD patients, including intractable preoccupations and failure to f lexibly adapt towards increasing cognitive load during working memory or executive planning tasks (Liang et al. 2016;Van Den Heuvel et al. 2005).Together, these findings may suggest a connectivity bias within the SN, leading to reduced regulation of DMN activity, and possibly increased engagement of the FPN in processing cognitions that are typically driven by DMN activity.

Task-related fMRI connectivity
Although both resting-state DMN hyper-and hypoconnectivity have been reported, only one report of task-related DMN hyperconnectivity was found during a monetary reward task (Koch et al. 2018).The DMN is active during rest and deactivated during cognitive task performance (Gusnard et al. 2001).Therefore, the reported hyperconnectivity could be a result of failure to deactivate the DMN in OCD.A similar phenomenon has also been reported in other mental health conditions such as schizophrenia (Pomarol-Clotet et al. 2008) and autism (Spencer et al. 2012).Alternatively, the DMN hyperconnectivity may stem from a failure of regulation by the SN within the TNM framework.Another study reported significantly higher connectivity within the SN during a multisource inference task (Cocchi et al. 2012).It is known that the SN represents major nodes of a central autonomic network supporting autonomic arousal and interoceptive awareness (Craig 2009).OCD patients may experience heightened autonomic arousal during the demanding rest-to-task transition periods, leading to hyperconnectivity within the SN.
In the context of the task-related findings within the TNM, contrasting observations were noted compared to resting-state findings.One study reported SN-DMN hyperconnectivity during error trials of an anti-saccade task (Agam et al. 2014).This finding suggests that individuals with OCD struggle to disengage from self-evaluative processes following errors, impeding their ability to redirect attention effectively to the task-at-hand (Stern et al. 2011).Furthermore, another study reported SN-FPN hypoconnectivity during a thought action fusion task (Lee et al. 2022).This further substantiates the hypothesis that cognitive inf lexibility in OCD patients leads to poor engagement of the task-positive FPN and impaired disengagement of the task-negative DMN during cognitive tasks (Gürsel et al. 2018).
In the task-related within network connectivity findings, the most consistently reported observation was increased FC within the FPN.Three studies reported significantly increased FC within the FPN in the OCD group compared to HC during a set shifting task (Kim et al. 2022), a cued task switching paradigm (Liu et al. 2023) and a cognitive reappraisal task (Picó-Pérez et al. 2022).Task switching and set shifting are both executive functions that involve the ability to shift attention between one task and another, and are thought to be subcategories of the broader concept of "cognitive f lexibility" (Jersild 1927).Similarly, the cognitive reappraisal task engages selective attention and cognitive control, serving to guide focus towards relevant stimulus features.The cognitive reappraisal task also involves the retention of reappraisal goals and the content of one's reinterpretation within the realm of conscious thought (Ochsner and Gross 2014).Therefore, FPN hyperconnectivity may be an exaggerated response to the cognitive demand during these tasks, potentially stemming from the inherent cognitive inf lexibility in OCD patients.Furthermore, given that OCD participants typically find these tasks more challenging than HC (Picó-Pérez et al. 2022), an increase in their network activation may occur as a compensatory mechanism to facilitate task performance.

Limitations and future directions
Both EEG and fMRI have strengths and limitations when measuring brain FC.While EEG excels in temporal resolution, providing millisecond-level timing precision, it has lower spatial resolution and therefore, lacks precision in pinpointing the exact location of neural activity (Song et al. 2015).fMRI has lower temporal resolution as it measures changes in blood f low, which are relatively slow compared to electrical activity recorded by EEG.However, fMRI captures deeper brain structures with high accuracy (Menon and Goodyear 2001).Our review has identified several contradictory findings, which may be related to these respective limitations.Additionally, while our review predominantly includes fMRI studies, ref lecting the current research landscape, the inclusion of EEG studies, although fewer in number, adds valuable insights into the temporal dynamics of brain activity in OCD.This disparity highlights the need for more future research using EEG to assess FC in OCD, and to adopt multimodal neuroimaging approaches, combining the strengths of both fMRI and EEG.Future studies could consider combining data from both modalities, or using a technique that combines the benefits of both, such as functional near infrared spectroscopy (fNIRS), magnetoencephalography (MEG), or simultaneous fMRI-EEG, potentially offering a more comprehensive understanding of the underlying FC findings in OCD.One of the significant challenges encountered in our review was the variability in network definitions across different studies, which could potentially impact the generalisability of our findings.For instance, some studies used different criteria or parcellation schemes to define networks, leading to variations in which brain regions are included within each network.To address this issue, future research should standardize network definitions or report the implementation of both methods as per recent multiverse analysis approaches (Steegen et al. 2016), which would enhance comparability and enable more robust identification of altered FC patterns.
A further notable challenge in synthesizing findings from both EEG and fMRI studies is the variability in preprocessing approaches.For example, in fMRI preprocessing, the use of global signal regression can introduce negative correlations in restingstate FC analysis, affecting the detection of overall FC patterns (Murphy et al. 2009a).In our review, the substantial heterogeneity in preprocessing pipelines across studies made it infeasible to conduct detailed subgroup analyses to evaluate the specific impact of each preprocessing method on the overall findings.
To enable future research to address this issue, we emphasize the importance of standardizing preprocessing approaches to enhance the comparability of results across studies, facilitate meta-analyses and improve the reliability of conclusions drawn from the data.
The analysis of connectivity measures can be approached through various techniques.In the EEG studies under review and those conducted previously (Miljevic et al. 2023), diverse analysis methods have been employed, posing challenges in comparing results and drawing accurate conclusions.It is worth noting that a recently published guide and checklist offer standardization for EEG connectivity analyses (Miljevic et al. 2021).Given that the majority of EEG studies included in this review scored poorly on this checklist (Supplementary Table S3), caution is warranted in interpreting their results.Furthermore, encouraging future studies to adhere to this guideline and employ optimal methods would enhance the consistency of results and facilitate meaningful comparisons across studies.Additionally, establishing a similar guideline for fMRI connectivity analysis with optimal techniques would be beneficial.A further limitation of our review is the variability in the definitions of frequency bands across the included EEG studies.This lack of standardization in frequency band definitions could potentially impact the comparability of results across studies.
A notable limitation of our review is the reliance on a qualitative summary of disrupted brain connectivity in OCD, without the use of quantitative methods (i.e.coordinate-based meta-analysis).Previous research has demonstrated the utility of such quantitative methods in evaluating disrupted functional connectivity networks across various psychiatric disorders (Sha et al. 2019).The variability in network definitions and seed points used across studies introduces significant heterogeneity, which we aimed to address by mapping reported brain regions to widely accepted functional networks.However, future research would benefit from standardizing network definitions and integrating coordinatebased methods to synthesize findings more precisely and elucidate potential brain connectivity mechanisms underlying OCD.
This review also included multiple studies examining FC before and after the application of neuromodulation methods, such as DBS (Figee et al. 2013) and behavioral therapies (Cyr et al. 2021;Fullana et al. 2017;Gao et al. 2021).Furthermore, there are several studies that investigated the effects of targeted TMS therapy on brain network connectivity (Cocchi et al. 2018;Mantovani et al. 2021).While not the main focus of this article, pre-to post-treatment FC changes and their relationship to treatment response could offer valuable insights into OCD mechanisms and potential therapies.For example, in our recent pilot study, individualized tACS demonstrated significant improvement in OCD symptoms (Perera et al. 2023a), adding to the growing body of research highlighting the promising outcomes of tACS therapy in OCD treatment (Grover et al. 2021;Klimke et al. 2016).This underscores the potential for future studies to explore alterations in brain FC associated with tACS therapy, providing valuable insights into its underlying mechanisms in OCD.
Our review focused on fMRI and EEG studies due to their prevalence and established protocols in OCD research.This focus allowed for a comprehensive and coherent synthesis of findings.However, we acknowledge the value of other neuroimaging techniques such as fNIRS and MEG, which offer unique insights into brain function.Future reviews could benefit from including these modalities to provide a more holistic understanding of OCD.Additionally, our literature search uncovered no task-related EEG studies that reported FC findings in OCD to date.Task-related EEG studies can provide important insights into neural mechanisms underlying OCD.Therefore, future research should investigate FC differences using task-related EEG data to enhance our understanding of the disorder's neural underpinnings.

Conclusions
OCD is a chronic condition significantly impacting the quality of life of patients, yet successful treatment remains challenging due to our limited understanding of its underlying pathophysiology.Neuroimaging studies, utilizing techniques such as EEG and fMRI, have examined brain FC in OCD.Our review considered 166 studies (10 EEG and 156 fMRI).In EEG studies, OCD exhibited lower delta and alpha FC, with inconsistent findings in other frequency bands.Resting-state fMRI studies, however, presented conf licting reports of both increased and decreased FC within the DMN and the sensorimotor CSTC circuit.Notably, decreased connectivity between the DMN and SN at rest suggests a potential link to the TNM, implicated in OCD pathophysiology.Task-related hyperconnectivity between the DMN-SN and hypoconnectivity between the SN-FPN point towards cognitive inf lexibility in OCD, potentially rooted in TNM dysfunction.In conclusion, our neuroimaging review unveils a complex FC landscape in OCD, highlighting complex interplays within and between brain networks.However, the presence of conf licting findings underscores the necessity for targeted research using standardized methods to deepen our understanding of the underlying pathophysiology of OCD.

Fig. 2 .
Fig. 2. a) Chord diagram illustrating decreased functional connectivity within and between large-scale brain networks.b) Chord diagram illustrating increased functional connectivity within and between largescale brain networks.In both figures, the connected network is indicated by the two edges of each line.The thickness of the lines relates to the cumulative number of OCD participants providing support for each finding.(DMN-Default mode network, CSTC-Cortico-striato-thalamocortical circuit, VMC-Ventral motivational circuit, SM-Sensorimotor circuit, DC-Dorsal cognitive circuit, FPN-Fronto-parietal network, SN-Salience network, VN-Visual network).

Table 1 .
EEG connectivity studies in OCD.

Table 2 .
Resting-state fMRI connectivity studies in OCD.

Author (year) OCD sample (Male, Female, Mean age, SD) Comparison sample (Male, Female, Mean age, SD) Key findings Involved neurocircuitry and direction of connectivity findings
Decreased FC within the DMN (L-PCC/lingual gyrus) and SM network (PCG) and increased FC within the FPN (DLPFC).

Table 2 . Continued Author (year) OCD sample (Male, Female, Mean age, SD) Comparison sample (Male, Female, Mean age, SD) Key findings Involved neurocircuitry and direction of connectivity findings
Increased FC in dorsal cognitive CSTC (dorsal striatum, vmPFC) in all age groups.Youngest age group showed decreased FC in CSTC loops involved in cognitive control (dorsal striatum/thalamus, dACC).

Table 2 . Continued Author (year) OCD sample (Male, Female, Mean age, SD) Comparison sample (Male, Female, Mean age, SD) Key findings Involved neurocircuitry and direction of connectivity findings
Tan et al. 2019;Tan et al. 2022; Velikova et al. 2010;Yazdi-Ravandi et al. 2018;Özçoban et al. 2018).Interpreting the results was challenging due to the limited number of studies.

Table 3 .
Task-related fMRI connectivity studies in OCD.